Making Data Talk: A Workbook for Effective Communication of Public Health Data, Lecture notes of Public Health

Download Making Data Talk: A Workbook for Effective Communication of Public Health Data and more Lecture notes Public Health in PDF only on Docsity! U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Making Data Talk: A Workbook Na tio na l C an ce r I ns tit ut e Table of Contents Introduction ............................................................................................................................................................ 1 Chapter 1: You CAN Make Data Talk and Be Understood ........................................................................... 2 Table 1.1 Contrasts Between Scientists and Lay Audiences ............................................................... 3 Table 1.2 Tips for Presenting Audience-Friendly Data ........................................................................ 4 Chapter 2: Use Communication Fundamentals to Your Advantage .......................................................... 5 Figure 2.1 Basic Communication Model ................................................................................................. 5 Table 2.1 Types of Sources ......................................................................................................................... 7 Table 2.2 Types of Channels ...................................................................................................................... 8 Table 2.3 Comparison of Selected Lay Audiences ................................................................................ 9 Chapter 3: Help Lay Audiences Understand Your Data ............................................................................... 10 Table 3.1 Audience Biases that Influence Quantitative Data Processing ........................................ 12 Practice Exercise .......................................................................................................................................... 14 Chapter 4: Present Data Effectively .................................................................................................................. 16 Table 4.1 Basics of Visual Symbols ........................................................................................................... 19 Practice Exercise .......................................................................................................................................... 21 Chapter 5: Use the OPT-In Framework to Make Your Data Talk ............................................................... 23 Table 5.1 Roles of Data in Communication ............................................................................................ 24 Practice Exercise .......................................................................................................................................... 26 Chapter 6: Show What You Know: Communicating Data in Acute Public Health Situations .............. 28 Table 6.1 Acute Public Health Situations: Communication Phases and Objectives ...................... 29 Table 6.2 Questions Lay Audiences May Have in Acute Public Health Situations ........................ 30 Table 6.3 Higher-Controversy Situations: Characteristics and Communication Implications ..... 31 Practice Exercise .......................................................................................................................................... 33 Chapter 7: Show What You Know: Communicating Data in Health Policy or Program Advocacy Situations ....................... 34 Figure 7.1 Public Policy Cycle .................................................................................................................... 35 Practice Exercise .......................................................................................................................................... 38 Conclusion ............................................................................................................................................................... 39 References ............................................................................................................................................................... 40 1 Introduction Communicating scientific data to lay audiences is difficult. Public health practitioners, researchers, clinicians, and others in the public health field often have the responsibility of communicating “the numbers” to individuals from all walks of life. How do you summarize and convey data so they make sense to someone who may not be familiar with the topic, let alone the basics of epidemiology or statistics? How do you package and present data to answer the question often asked by busy people with competing demands and time constraints: why should I care? The National Cancer Institute (NCI) is pleased to introduce Making Data Talk: A Workbook, which is based on the groundbreaking book Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press.1 This workbook is designed to be a companion piece that enhances the information presented in the text by Drs. David E. Nelson, Bradford W. Hesse, and Robert T. Croyle, NCI researchers with significant expertise in their own fields. The information presented in Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press reflects a careful synthesis of research from many disciplines, so the principles described in the book can be applied to a variety of public health issues, not just cancer. This workbook complements the various communication and education tools and materials available through the NCI. The content presented in the following chapters will take you through communication concepts, an easy-to-understand framework for communicating data, and the application of that framework to actual public health situations. Many chapters also include practice exercises that use real-world examples to reinforce key concepts and help you apply what you have learned. We hope this workbook will serve as a guide for those looking to successfully communicate scientific evidence to improve public health. Office of Communications and Education National Cancer Institute 4 Table 1.2 Tips for Presenting Audience-Friendly Data After reading this chapter, you should be able to recognize that effective communication with audiences outside of the scientific community requires consideration of how those audiences differ from the scientific community and how communication can be modified to account for those differences. For further detail on concepts presented in this chapter, refer to Chapter 1, Introduction, of Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press. Tip Example/Explanation • Avoid terms not frequently used outside of the scientific community. Cohort, longitudinal • Avoid terms with multiple meanings. Surveillance • Avoid science and math concepts that can be misunderstood. If these term(s) or concepts must be used, be sure to explain them in an easy-to-understand way. Proportions, relative risk • Focus on the main message instead of detailed scientific arguments or outcomes. When making decisions, many people use heuristics (shortcuts) rather than the rational decision-making model used by most scientists.2 • Explain how the data may impact audiences. Demonstrating impact can help audiences understand why the data are relevant to them. • Present data in a distinctive way that helps you gain the attention of your audiences. For a majority of people in the United States, health issues are of moderate-to-low interest.3 Presenting relevant and interesting information can reduce the likelihood that people will filter it out due to lack of interest. 5 CHAPTER TWO: Use Communication Fundamentals to Your Advantage All efforts to share information—whether discussing a simple issue or a complex topic—consist of a few basic communication elements. By understanding these elements and how they work together, you can make informed choices about your communication approach. After reading this chapter, you will be able to: ➥ Identify and differentiate the four main elements of the basic communication model. ➥ Name three lay audiences key to public health communication. ➥ Recognize how messages can be developed to support a storyline. Consider the basics A variety of elements are involved in the basic framework of communication. Although many more complex models of communication exist, this workbook uses the basic communication model presented in Figure 2.1 as the foundation for discussion. Figure 2.1 Basic Communication Model This basic communication model presents four main elements: 1) Messages, or WHAT is used to convey information (e.g., words, symbols, or pictures). 2) Sources (or senders), or WHO SENDS the message (e.g., individuals or organizations). 3) Channels, or HOW messages are sent (e.g., newspapers, conversations, or e-mail). 4) Audiences (or receivers), or WHO RECEIVES the message and interprets it. Source and channel Message Context Context Audience (receiver) Source: Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press by David E. Nelson, Bradford W. Hesse, and Robert T. Croyle (2009), Figure 2.1, p. 31. By permission of Oxford University Press, Inc. (www.oup.com). See References for additional sources. 6 This workbook primarily focuses on helping people who work in public health (the senders) effectively communicate quantitative data as part of the health messages they send to the general public, policy makers, and the press (audiences) using various channels. In order to make the best decisions about the individual elements of the communication process (e.g., messages, channels, etc.), you should first consider the following: ➥ Purpose (i.e., why the message is being communicated). There are four purposes for communicating public health information: to increase knowledge, to instruct, to facilitate informed decision-making, and to persuade. It is important to know which of these applies to the messages you are sending. ➥ Strategy (i.e., the approach for gaining attention). Some communicators use an active strategy, such as employing a mass media campaign or encouraging word-of-mouth communication. Others use a passive strategy, such as adding information to a Web site and relying on information-seeking audiences to find it. The “push-pull” model combines both strategies by sending messages to audiences (the push: active), while also making information and materials available to interested parties (the pull: passive). ➥ Context (i.e., factors that may influence receipt and/or interpretation of the message). Contextual factors—including other sources of information, personal experience, and competing priorities—are often outside the control of those sending messages. These factors can have influence at various points during the communication process and can even prevent effective communication. Determining your purpose, planning a strategy, and considering the context are all crucial steps in the communication process. In fact, these elements are three of the five fundamental pieces of the “Plan” step in the OPT-In framework that will be presented in Chapter 5. Messages Messages – and the storylines they support – play a critical role in both the basic communication model presented in this chapter and the OPT-In framework presented in Chapter 5. The term “storyline” must be defined and explained before messages can be developed and communicated to audiences. In this case, the term “storyline” refers to the major conclusion(s) that scientists and other health practitioners want audiences to understand. In other words, the storyline is the science-based bottom line. This differs according to the type of information the story is based on. Once storylines are determined, messages must be developed. Messages – chunks of information that support the storyline – should be based on scientific knowledge and understanding. Each message should be able to stand alone by communicating a single idea, but, collectively, the messages should provide rationale for the larger theme (i.e., the storyline). ◆ “Settled science,” or science that has received a clear consensus based on many studies over time, makes for the strongest storylines since it provides a clear rationale. As a result, messages supporting settled science storylines can be persuasive or instructive in nature. ◆ Science that has little supporting knowledge and/or no consensus among scientific experts is more difficult to address. Messages supporting these types of storylines should focus on increasing knowledge or informing the decision-making process. 9 Table 2.3 Comparison of Selected Lay Audiences Audience segmentation refers to the process of dividing an audience into smaller subgroups based on shared characteristics (e.g., demographic information, geographic location, habits, and behaviors). Segmentation is a part of audience analysis—research that helps you better understand the people with whom you wish to communicate. Audience analysis can aid in planning your communication approach, thus, it is one of the five fundamental pieces of the “Plan” step in the OPT-In framework. After reading this chapter, you should have a better understanding of the basic model of communication and its four elements: messages, sources, channels, and audiences. For further detail on concepts presented in this chapter, refer to Chapter 2, Communication Fundamentals, of Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press. Source: Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press by David E. Nelson, Bradford W. Hesse, and Robert T. Croyle (2009), Table 2.2, p. 49 and Table 2.3, p. 54. By permission of Oxford University Press, Inc. (www.oup.com). See References for additional sources. Individual characteristics Occupational and institutional factors Regular sources of information General public Variable by audience subgroup, but common factors include: • Level of interest in and involvement with health issues • Geographic location • Varying levels of education • Socioeconomic status • Health insurance status • Existing health beliefs, social beliefs, and worldviews • Gender • Age • Various social networks and cultures Variable by audience subgroup, but trusted sources may include: • Healthcare providers • Television news • Internet Web sites • Other people (e.g., friends, relatives, neighbors, co-workers) • Radio/ethnic media Policy makers • Ambitious, hard-working, savvy • Attuned to financial implications • Intuitive decision-making is common • Want certainty from experts • Public vs. private systems • Elected vs. appointed individuals • Formal and informal processes • Public policy typically made by legislators, executives, or administrators • Interpersonal relationships crucial • Rely on gatekeepers • Busy and subject to multiple communication efforts and requests • Interpersonal sources • Attend to relevant news media coverage Press • Usually have progressive “mainstream” values and beliefs • Concerned about individual freedom issues • May be intimidated by scientists or health professionals • General reporters, specialty reporters, and editorialists • Business considerations: attuned to topics of interest to the public • Short deadlines common • Differences between specific news media (e.g., newspapers, TV) • Certain characteristics make stories more “newsworthy” (e.g., local tie-in) • Prefer personal stories (narratives) • Much competition for news space • Follow news outlet “leaders” (e.g., elite papers such as The New York Times) • Preselected list of trusted expertsPress 10 When people receive messages, they process and interpret them based on their own literacy level, tendencies, and biases. As a result, these factors must be considered and addressed when communicating quantitative data to audiences. After reading this chapter, you will be able to: ➥ Identify audience tendencies that can influence how people receive data. ➥ Describe biases that audiences can have when interpreting data. ➥ Recognize techniques to overcome these tendencies and biases. Be aware of audience tendencies People are not always well-prepared to receive and process messages containing quantitative data. Quantitative literacy (i.e., the skills required to apply mathematical operations) varies from person to person, and even the most educated audiences may have only a basic or intermediate level of familiarity with mathematical concepts. Common mistakes people make when interpreting numbers include: ➥ Misunderstanding probability estimates5 (people may believe that a risk of 1 in 200 is greater than a risk of 1 in 25). ➥ Misunderstanding percentages. ➥ Improperly converting proportions to percentages.6 To account for differences in quantitative literacy, health communicators should simplify messages, provide additional explanation, or modify their approach to increase audience understanding. In addition to literacy considerations, health communicators should also be aware of general information processing factors that, although not specific to data or public health topics, can be strongly influential as people process quantitative data. Here is a list of these tendencies along with explanations and examples. Cognitive processing limits. Individuals have a limited capacity to process large amounts of information at one time and simplify or “chunk” the information to which they are exposed. ◆ The 7-digit telephone numbering system was based on research suggesting that people can optimally retain only 7 (±2) discrete pieces of information at a time.7 Satisficing. People tend to limit the amount of mental energy they spend obtaining information until they believe they have “enough” for their purposes.8 ◆ Studies show that visitors will usually leave a Web site within 15 minutes or less if they do not find the information they need.9 CHAPTER THREE: Help Lay Audiences Understand Your Data 11 Expectations of experts and the challenge of uncertainty. Most lay audiences want experts with experience and credentials to provide definitive, prescriptive information.10 ◆ To use a non-health example, people look to mechanics to definitively diagnose automobile problems — instead of estimating that there is a 30 percent chance that the alternator is the problem — as well as to recommend specific solutions. Processing risk information. Many people misunderstand concepts related to risk, such as absolute risk, lifetime risk, and cumulative risk.11 ◆ Most people do not recognize that repetition of low-risk behavior — such as failing to wear a seat belt with every car ride — increases a person’s cumulative risk of adverse outcomes during their lifetime. Framing. “Framing” is presenting data in a way that is consistent with common public frames or models. ◆ Emphasizing the possibility of colon cancer over the minor discomforts of a colonoscopy is an example of a loss frame. ◆ Associating rewards, such as losing weight and looking fit with exercise, is an example of a gain frame. Scanning. People often do a quick scan of written or visual material to decide if it interests them, draw conclusions about what the major points might be, and try to identify the bottom line.12 ◆ When an Internet search for specific information returns hundreds or thousands of potential Web sites, people scan the first few results before deciding which link to follow. Use of contextual cues. People tend to look for cues to help them better process and understand information, especially in cases where the data presented is complex, detailed, or in an unfamiliar format.13 ◆ Regular reports on breast cancer data can be of more use to audiences by highlighting what has changed since the last report. Resistance to persuasion. People have a natural resistance to persuasion and often engage in a practice of defensive processing, an approach that blunts messages that are inconsistent with current behavior. ◆ Smokers may blunt messages emphasizing that smoking is bad since those messages are inconsistent with the smoker’s own attitude toward tobacco use. Role of emotion. Emotions have the potential to be a motivating influence on behavior by heightening arousal, orienting attention, and prompting self-reflection.14 ◆ Communicating that 440,000 Americans will die from smoking in a given year may cause a variety of emotional reactions based on the reader’s own relationship or attitude towards smoking. 14 Practice Exercise The following five scenarios describe a situation where a communicator uses a specific communication skill or strategy to overcome an audience tendency or bias. Review the scenarios and select the answer which correctly identifies the tendency or bias that the communicator sought to overcome. 1) A university research department decides not to release findings from a Phase I clinical trial because of concern that the promise of a pharmaceutical treatment showing that 80% of participants had complete resolution of their disease symptoms may create great excitement that will be followed by disappointing results in Phase II. This decision shows a consideration for which of the following: a. Resistance to persuasion b. Anchoring and adjustment bias c. Failure to consider randomness d. Satisficing 2) To help explain a new report that conveys the latest statistics related to breast cancer incidence, communicators develop a graphic that compares this year’s figures to figures from the previous five years. This graphic helps address the following: a. Processing of risk information b. Role of emotion c. Use of contextual cues d. Satisficing 3) A government health agency publishes a press release about a complex genetics research project. Although many endpoints were involved in the study, the communicator decides to focus only on one or two data points. This strategy is designed to address which of the following: a. Information framing effects b. Cognitive processing limits c. Use of contextual cues d. Role of emotion 15 4) During a media interview, a study’s lead scientist answers a question related to the brain’s role in the development of addiction. After the reporter takes notes, the scientist reiterates that a particular brain area doesn’t cause addiction, but that it plays a role in the development of addiction. This shows the scientist’s attempt to overcome which of the following: a. Information framing effects b. Processing of risk information c. Failure to consider randomness d. Correlation equals causation 5) A doctor conducts an interview to discuss health conditions affecting women. During the interview, the doctor acknowledges that many women perceive breast cancer to be the primary killer of women. He provides statistics showing that heart disease kills more women than breast cancer and then reiterates that women should be just as aware of heart disease as breast cancer. This technique helps overcome the following: a. Resistance to persuasion b. Scanning c. Failure to consider randomness d. Anchoring and adjustment bias Practice Exercise Answers: 1. B (Anchoring and adjustment bias) 2. C (Use of contextual cues) 3. B (Cognitive processing limits) 4. D (Correlation equals causation) 5. A (Resistance to persuasion) 16 As a communicator, think more about what you want your audience to understand and less about what you want to say. Your task is to use the tools of scientific communication—words, symbols, and numbers—to help people build knowledge around the issues being communicated. Further, this task has to be accomplished accurately and ethically. You have heard the expression, “perception is everything.” In this case it means that your understanding of the perceptual processes of humans is critical to help appropriately select and effectively use tools for communicating data. While reading this chapter, keep the following research18 in mind: ◆ People tend to perceive items that are close to each other in a visual field as being somehow related. You will need to consider how “proximity” of elements within your data presentation can promote understanding. ◆ Our eyes have a tendency to follow lines and directions implied by separate elements within a visual field. “Continuation” is another critical factor to consider when designing data presentations. For example, the continuation of lines (versus bars) in a graph may help better tell your story. Likewise, effective use of headlines, headings, and sub-headings facilitate a reader’s understanding of how information is presented in a document. ◆ People tend to “fill in” information that is not specific in a presentation to help them make sense of the presentation as a whole. This process of “closure” is effective when the correct details are filled in, but it can be ineffective and even dangerous when people fill in the wrong information. You can use strategies to reduce the chance that people will use closure in a potentially harmful way. In this chapter, you will learn how to capitalize on or overcome these tendencies as you read about several data presentation formats. The basics of each format – when to use different formats, how to use them effectively, and the do’s and don’ts of their application – are summarized in this chapter. After reading this chapter, you will be able to: ➥ Evaluate graphical presentations to identify features that help audiences understand data and features that could be added to enhance a data presentation. ➥ Describe how to effectively use pie charts, bar charts, line graphs, arrays, and visual scales to promote the understanding of data. CHAPTER FOUR: Present Data Effectively 19 Table 4.1 Basics of Visual Symbols Pie Charts The basics • Show proportions/percentages, especially their comparison, for a total of 100% • Display a “whole” with smaller parts and how they relate to each other • Good for highlighting the largest or smallest piece of something Do • Make sure the largest slice is pointed at 12 o’clock • Display slices clockwise in descending order • Use short labels and position them horizontally and outside the pie Do not • Show more than six slices Bar Charts The basics • Bars represent a group of data with heights/lengths measured using percentages, dollars, etc. • Axes allow the display of two or more individual numeric values • Good for displaying magnitude or comparative magnitude between groups of data • Can show relative differences or patterns between/across groups • Horizontal orientations allow text labels to be placed in an easy-to-read position • Vertical orientations are best for showing a comparative rise or fall in counts over levels of one or more variables Do • Use six or fewer bars per chart • Use color/shading with strong contrast • Use a bar or line to show a baseline value • Use short and easy-to-understand titles, labels, key messages • Select beginning and ending values and interval widths for axes that represent patterns in the data without distortion Do not • Use segmented or stacked bar charts to demonstrate how proportions compare to the whole • Overlay line representation on top of the bars to indicate variance estimates or confidence intervals Line Graphs The basics Good for showing: • A connected sequence of data, such as trends over time • Before and after differences • If numbers are going up, down, or remaining stable Do • Use arrows or text to highlight key events or data • Place labels close to their lines • Include baseline data for comparison purposes • Use short and easy-to-understand titles, labels, key messages • Select beginning and ending values and interval widths for axes that faithfully and ethically represent patterns in the data without distortion Do not • Add unnecessary labels or symbols • Use more than four trend lines 20 Icons/Arrays The basics • Individual graphical elements, such as circles, human figures, etc., are used to represent quantitative data • Good for showing rankings or ratings in tabular display • Good for displaying probability data representing absolute risk Do • Use body-shaped figures to represent humans when it seems fitting • Place icons representing numerator values contiguously • Use common denominators between two arrays • Highlight numerator icons Do not • Randomly place icons representing numerator values unless the sole goal of the array is to demonstrate randomness • Distort data; make sure to carefully increase the height and width of icons when showing change in magnitude Visual Scales The basics • Use where numbers are ordered and there are equal distances between intervals; or where numbers are ordered but the intervals between values may be uneven • Use scales that are familiar, such as thermometers and meters with meaningful colors and arrows or lines showing a range of values • Use scales to visually represent risk (probability) data, and absolute risk data and comparisons Do • Provide anchoring information (lines or arrows) to give contextual cues and orient the audience to baseline data • Include short titles and key messages • Follow conventional approaches for data presentation (e.g., red to indicate higher levels of threat in the United States) Do not • Underestimate the role of emotion and perceived inequity if scales are used in involuntary exposure situations • Include too much information Data Maps The basics • Help illustrate how frequencies are distributed geographically • Support interpretive tasks, such as comparisons • Use colors or shading to show data ranges Do • Use lines to demarcate discrete entities (geographic borders) • Write clear titles and make labels short and to-the-point but complete • Use callouts to highlight some regions when necessary • Use color to enhance attractiveness and illustrate variation in data • Use a sequential progression of colors from light to dark Do not • Place red and green side by side • Use more than three to four colors or assume that color schemes displayed on computer monitors will looks the same in print Table 4.1 Basics of Visual Symbols continued 21 Practice Exercise Consider the following visual displays that were found on federal agency Web sites. Demonstrate what you have learned about the optimal design and use of visual displays by evaluating the samples and answering the associated question. Question 1: How can this bar chart be modified to make it more effective? Current Asthma Prevalence Percentages by Age, Sex, and Race/Ethnicity, United States, 2008 C hi ld 9 .4 % A du lt 7 .3 % M al e 7. 1 % Fe m al e 8 .5 % W hi te 7 .8 % B la ck 1 0 .3 % H is pa ni c 5 .8 % 12 10 8 6 4 2 0 Age Sex Race/Ethnicity Current Cigarette Smoking Among Women Age 25 and Older, by Education Level, 1995-2006* Question 2: Is there a better way to present the data found in this line graph? Explain your answer. *Estimates are age-adjusted. Less than HS 26.0 23.4 19.6 17.9 7.2 HS Diploma or GED Some College College Degree or Higher Total 40 30 20 10 1995 2000 2002 2004 2006 P er ce nt ag e of W om en 24 Table 5.1 Roles of Data in Communication OPT-In: Organize, Plan, Test, Integrate The authors of Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press have developed a framework to help communicators plan and execute their data-related communications. The framework employs a mnemonic (or memory) device – OPT-In – which stands for Organize, Plan, Test, and Integrate. A brief overview is provided on the next page and the exercise at the end of this chapter is designed to help you understand and internalize the framework’s application. Role Explanation/Example Raise awareness • Used to communicate that a problem exists, why it exists, how many are affected, and how it can be addressed. • Data can be simple descriptive statistics, such as X people are affected by Y disease; or X people have diabetes, a major risk factor for chronic kidney disease. Reduce level of concern • Used to help people gain perspective about what does and does not constitute a substantial level of health risk. • May be used in clinical settings to help people understand the impact of certain behaviors or exposures or the benefits of a certain treatment. Explain (cause and effect) • Used to show or refute association or cause-and-effect relationships and their magnitude or provide a basis as to why certain conclusions were reached. • Causal data, for example, can be used to support a storyline that provides hope: X percentage of people who are treated with Y never experience disease symptoms. Provide contextual information • Used to improve understanding of a public health issue, usually with some type of comparison to an overall population value. • May be used to demonstrate how the prevalence of a condition has or has not changed over time or how one state is impacted by an exposure compared to how another state is impacted. Predict • Used to communicate projected or expected effects of a policy or program or the ending of one. • Data may be used to estimate how many people are expected to be positively or negatively impacted by a change. Evaluate • Used to communicate observed impacts of a policy or program or of their discontinuation. • Data may be used to show how many people were impacted by X program. Maintain awareness • Used to remind people of something they already know. • Data may be used to point out how many lives are saved each year by using seat belts or how many viral transmissions are prevented due to the simple act of hand washing. Source: Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press by David E. Nelson, Bradford W. Hesse, and Robert T. Croyle (2009), Table 5.1, p. 180. By permission of Oxford University Press, Inc. (www.oup.com). See References for additional sources. 25 Organize. During this crucial first step of the framework, communicators must develop a clear understanding of the scientific knowledge and the level of consensus among scientists. If the state of the science is unknown, a formal review of the literature will be needed. Otherwise, a review and synthesis of the consensus among scientists will be adequate. The science will then be used to develop the storyline, which is essentially the major conclusion about the science. It is critical to ensure that the storyline communicates exactly what is intended (about colonoscopy, the HPV vaccine, etc.) without causing confusion or limiting the potential impact of the message—which speaks to the need for testing (see below). While organizing, the communicator will also determine whether or not data will be included in message development. If data are included, the communicator must take steps to ensure their relevance and clarity. Revisit Chapter 2 of this workbook to review information on storylines and message development. Plan. The second step focuses on ensuring that the storyline is accurate and strategically presented to audiences. Your plan may be brief or long, depending on the situation. The five planning components covered in Chapters 2 and 3 of this workbook are the focus of the “Plan” step of this chapter’s exercise and include: 1) Determining the purpose for communication. 2) Analyzing the audience(s). 3) Considering the context in which communication will occur. 4) Developing a preliminary message (which may or may not include data). 5) Planning a strategy to reach audiences. Test. The third step of the framework encourages message and usability pre-testing. Extensive testing often is not possible, but even some formative and/or usability testing may mean the difference between succeeding and failing at your communication task. ◆ Formative testing involves getting feedback from people who are part of your target audience while you are developing messages and materials and selecting communication channels before actually starting your communication activities. Examples of testing strategies include conducting interviews or focus groups, implementing surveys, and collecting feedback cards to determine audience preferences and understanding of messages. ◆ Usability testing is conducted to ensure a communication product’s ability to support the audience member’s task. Testing involves observing anticipated “users” while they try out a decision aid, Web site, or application to identify problems that can be corrected before actual implementation. Integrate. The fourth and final step focuses on integrating communication efforts and integrating messages within a broader context of current scientific understanding. Communicators must coordinate efforts within and across communication channels for a defined communication effort. It is critical to portray scientific findings and conclusions with accuracy and clarity and in a way that makes them usable and useful to audience members. The Integrate section of this chapter’s practical exercise will help you think through this step. 26 Some other things to consider ◆ Data should be used sparingly to limit cognitive burden and presented in formats that are familiar to the audience (e.g., pie charts). ◆ Framing messages as gains/benefits or losses/negative effects can be highly influential. For primary prevention, emphasize the positive effect of the behavior; for secondary prevention (e.g., screening), emphasize the negative consequence of failing to be screened. ◆ The order or sequence of data will impact how information is remembered. For example, the first and last numbers presented are most likely to be remembered.22 ◆ Identify and make numbers ‘stand out’ by showing how they are unique or novel. Doing so will help demand attention and can promote newsworthiness. ◆ Integrate words, numbers, and symbols. After reading this chapter, you should have a general understanding that applying the OPT-In framework to a communication task can result in presentations that promote audience members’ understanding of data. For further detail on concepts presented in this chapter, refer to Chapter 5, Putting it All Together: Communicating Data for Public Health Impact, of Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press. Practice Exercise The National Cancer Institute administers the Health Information National Trends Survey (HINTS), which is a biennal, cross-sectional survey of a nationally-representative sample of American adults that is used to assess the impact of the health information environment. Specifically, HINTS measures how people access and use health information, how people use information technology to manage health and health information, and the degree to which people are engaged in healthy behaviors. Use the following exercise as an opportunity to apply the OPT-In framework to a real-world communications task. A portion of a HINTS brief, which provides a snapshot of noteworthy, data-driven research findings, is provided here. This brief explores factors associated with accurate knowledge about lung cancer and the negative effects of tobacco use through the analysis of HINTS survey data. Read the results outlined in the brief. You want to communicate the results to the regional health director to support development of an educational campaign but are unsure about your messaging, your presentation, and how you will integrate your messages in a broader context. Use the questions on the next page to help you prepare to communicate your data. Read the entire brief by visiting: http://hints.cancer.gov/brief_11.aspx. 29 Check for understanding: The March 2011 earthquake in Japan and its aftermath (e.g., a damaged nuclear reactor) is an example of an acute public health event. Review the list again to identify how many of these factors helped define the disaster in Japan as an acute public health event. Communication process Responses to acute public health situations are known by several names — crisis, risk, emergency, and disaster communications — and require swift but well-conceived message development and execution. Communicators must consider the following when communicating in such situations: Communication phases and objectives. When faced with the prospect of communicating about acute public health events, it can be helpful to take a phased approach, such as one that has been effectively applied to many crisis situations. Approach the communication task as steps that can be taken before, during, and after the acute public health situation (crisis). See Table 6.1 for the steps or objectives to be executed during each phase. Consider using this approach in conjunction with the OPT-In framework. Table 6.1 Acute Public Health Situations: Communication Phases and Objectives Phase Objectives Pre-Crisisa 1. Be prepared 2. Foster alliances 3. Develop consensus recommendations 4. Test messages Crisis (Initial) 1. Acknowledge event and uncertainty 2. Explain and inform audiences, in simple terms, about risk(s) 3. Establish organizational/spokesperson credibility 4. Provide emergency courses of action (i.e., how and where to get more information) 5. Commit to providing stakeholders and public with continued communication Crisis (Maintenance) 1. Help people more accurately understand their own risks 2. Provide background and encompassing information to those who need it (e.g., how it happened, whether it has happened before, how to prevent it in the future, will recovery occur, will there be long-term effects) 3. Gain understanding and support for response and recovery plans 4. Listen to stakeholder and audience feedback and correct misinformation 5. Explain emergency recommendations 6. Empower risk/benefit decision-making Post-Crisis (Resolution and evaluation) 1. Evaluate communication plan performance 2. Document lessons learned 3. Determine specific actions to improve crisis systems or the crisis plan 4. Consider ways to better educate the public response in the event of future similar emergencies 5. Honestly examine problems and mishaps and then reinforce what worked in the recovery and response efforts 6. Encourage support for policies or resource allocation to promote effective responses to future acute situations 7. Promote activities and capabilities of the organization a Note. “Crisis” and “event” are often used interchangeably to describe communication phases. Source: Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press by David E. Nelson, Bradford W. Hesse, and Robert T. Croyle (2009), Table 6.3, p. 227. By permission of Oxford University Press, Inc. (www.oup.com). See References for additional sources. 30 Questions to guide communication. Those responsible for communicating about acute public health situations will need to tailor messages for the public/lay audiences, the media, health professionals, and various other groups. Experts have developed a list of questions (see Table 6.2) that the public may have during acute public health situations. Communicators can use them to guide the development of messages. Table 6.2 Questions Lay Audiences May Have in Acute Public Health Situations Some other things to consider The following message content and delivery guidelines should also be considered in acute public health situations: ➥ Provide accurate information about the situation, decisions being made, and actions being taken. ➥ Use simple and nontechnical language. ➥ Use consistent messages. ➥ Provide messages quickly and regularly. ➥ Demonstrate empathy, caring, honesty, openness, commitment, and dedication. ➥ Acknowledge the uncertainty of the situation and audience fears or concerns. ➥ Correct misinformation quickly. ➥ Do not be overly reassuring. 1. What is the problem and how serious is it (what is happening)? 2. Are my family and I (or community members, friends) safe? 3. Is there a chance that I, or those who matter to me, could be affected? 4. What should I (or others) do to protect myself (themselves)? 5. Who or what caused this problem (how or why did this happen)? 6. What does this information mean (interpretation)? 7. What can we expect will happen? 8. Can the problem be fixed? 9. What is being done to address the problem and why? 10. How are those who are affected getting help? 11. Is the problem being contained (e.g., is the intervention or action working)? 12. When did you begin working on this problem (when were you notified about it, when did you determine that there might be a problem)? 13. Did you have any forewarning that this might happen? 14. Why wasn’t this prevented from happening? 15. What else can go wrong (“worst-case” or “what-if” scenarios)? 16. Who is in charge? 17. What is not yet known? 18. What bad (or good) things aren’t you telling us? 19. Who can I turn to, or where can I go, to get more information? 20. When will you be providing us with more information? 21. How much will it cost to fix this problem?a 22. Who is or will be responsible for paying to fix this problem or compensate those affected for their losses?a a Note: Primarily from policy makers. Source: Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press by David E. Nelson, Bradford W. Hesse, and Robert T. Croyle (2009), Table 6.4, p. 228. By permission of Oxford University Press, Inc. (www.oup.com). See References for additional sources. 31 Controversy Potential Acute public health situations can be categorized based upon their potential for controversy—a factor that will influence communication decisions. The following factors distinguish lower- and higher-controversy situations from one another. Potential lower-controversy situations ◆ Include localized infectious disease outbreaks, natural disasters, or acute chemical exposures. Specific individuals and organizations are often identified as responsible for the situation. ◆ Usually have a well-defined and identifiable health outcome for which a strong scientific consensus exists. The outcome is occurring at a higher rate than expected and has an identifiable cause with a plausible and strong cause-and-effect relationship. The exposure, outcome, and cause-and-effect relationship are recognized in a relatively short period of time. ◆ Public health interventions or measures, if employed, fall within the acceptable normative beliefs of the public and policy makers. ◆ Communicating about lower controversy situations may require no or minimal communication involving data. Rather, recommendations for protecting one’s health may be more appropriate in lower-controversy situations. Potential higher-controversy situations ◆ Include extended outbreaks, scientific consensus at odds with an audience’s strongly-held beliefs, or higher levels of scientific uncertainty with or without adequate or widely accepted resolutions. Table 6.3 identifies how and why higher-controversy potential situations result and the related communication implications and insights. Table 6.3 Higher-Controversy Situations: Characteristics and Communication Implications In general, potential higher-controversy situations may generate intense lay audience interest, which may make audience members more motivated to understand data and require relatively more extensive data communication efforts. Common causes of higher-controversy situations Communication implications Definitive cause of an infectious disease, for example, was not identified early. Controversy increases as health effects become more serious, the number of people or geographical area grows, and the situation endures. Journalists often seek details about scientific methods and analytic approaches to support the “mystery” they’re reporting. A scientific consensus’s explanations, conclusions, or recommendations are unacceptable to various audiences. This is common for environmental issues, product exposures, and scientific bombshells. Communications are difficult because messages may contradict previous consensus recommendations from experts. Messages also may challenge strongly held beliefs. Adequate or widely acceptable resolutions cannot be achieved due to a high level of scientific uncertainty. This is common for environmental, occupational, or product safety or consumer protection issues. Communicators must address anxiety and fear among audiences. Some situations may require extensive and long-term communication efforts (for months to years). 34 CHAPTER SEVEN: Show What You Know: Communicating Data in Health Policy or Program Advocacy Situations Public health is often influenced by efforts of individuals (advocates) and organizations that either support or oppose specific policies or programs that affect the public’s health. Advocacy activities can be short- or long-term and may involve laws, regulations, or resources allocation. Advocacy distinguishes itself from other public health situations in two ways: 1) persuasion is the primary purpose for communicating information, including data, and 2) policy makers are usually the primary audience, with the press and public being secondary. This chapter provides a brief overview of the policy development process, the advocacy communication process, and considerations for using data in advocacy situations. This information is followed by an opportunity to apply what you learn. After reading this chapter, you will be able to: ➥ Describe the steps in the public policy cycle and the advocacy communication process. ➥ Prepare to communicate support for a new local law that will impact public health. To understand the communication process in advocacy situations, one must first understand the public policy cycle, which includes four interdependent phases. During the problem identification phase, policy makers recognize that a particular problem or issue must be addressed. Policy makers then shift into the policy formulation phase, where they consider potential options and decisions about how to address the problem. Next is the policy implementation phase, where those responsible for carrying out the policy interpret and make decisions about the policy. Once enacted, the policy enters the policy evaluation phase, where a formal or informal assessment of the policy is carried out. The four phases are shown below in Figure 7.1, along with examples of what may take place during each phase if a community were to address local obesity rates. 35 Figure 7.1 Public Policy Cycle Feedback / maintenance Policy evaluation Policy formulation Policy implementation Problem identification (issue definition) • Obesity is on the rise in Anytown, USA • A diet high in calories and/or fat appears to be an important factor in obesity, along with a sedentary lifestyle • Local government officials receive and discuss feedback from community members on an ongoing basis • The health department tracks impact on obesity rates over time • Merchants and citizens have an opportunity to advocate for and oppose enactment of a law requiring restaurants to post calorie information on their menus • Elected officials vote to enact the law • City leaders inform restaurant owners of the new law’s requirements/timing • Restaurants comply with the law and are spot-checked by local officials Communication process in advocacy situations Effective advocacy requires attention to the communication process. Steps include the following: ➥ Conduct research to learn about policy makers (and their gatekeepers), as well as their information sources and preferences. Use Web sites of elected representatives, and talk with their staff members. ➥ Understand formal and informal communication processes. These include processes for presenting at committee hearings (formal), and how policy makers’ gatekeepers can make decisions that promote or derail your efforts (informal). ➥ Consider timing. Use common sense to guide decisions about when to communicate or not to communicate with policy makers. Capitalize on the use of focusing events (e.g., legislative hearings), and avoid communicating with policy makers when they are distracted by other events. ➥ Coordinate with allies. Work with like-minded individuals or organizations to collaboratively communicate your message to, and with, advocacy organizations. ➥ Select best sources for information and message delivery. People’s opinions are often based on their perception of the source, so individuals or organizations who deliver messages must be considered trustworthy and not self-serving. ➥ Gain media attention. Policy makers will attend to issues, policies, and programs that are getting media attention. ➥ Follow up. Provide needed or requested information, and express appreciation for the individual’s time and consideration. Source: Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press by David E. Nelson, Bradford W. Hesse, and Robert T. Croyle (2009), Figure 7.1, p. 268. By permission of Oxford University Press, Inc. (www.oup.com). See References for additional sources. 36 Message delivery in advocacy situations Similar to other situations, advocacy-related communication requires attention to message delivery. When possible: ➥ Be brief and quickly get to the main point. ➥ Be definitive and avoid technical jargon. ➥ Use real-world examples and localize data and narratives. ➥ Anticipate opposition arguments, be prepared with responses, and provide short handouts with key points and contact information. Scientific data and advocacy While scientific data are not the only factor that can impact policy makers, data can indeed be used by scientists to effectively influence and persuade policy makers and the public. Refer again to the OPT-In framework, presented in Chapter 5, which is useful for planning and implementing communications in advocacy situations. During the planning process, determine whether or not the presentation of data will support identified themes and messages. Previous chapters in this workbook outlined how data can serve various roles, depending on the situation and the communicator’s needs. In policy advocacy, public health data can be used to: ➥ Raise awareness. Surveillance or trend data can be used to define a problem or issue, to demonstrate that a problem exists, that it is important or serious, and/or that it impacts a large number of people. Gloom (negative message framing) is a theme often used to raise awareness, particularly when communicators want to shame policy makers into action. ➥ Show cause and effect. Data that are typically derived from research are used to show that situations previously thought to be inevitable or random can now be controlled in some way (e.g., through a new program, policy, screening, diet). Control and hope (positive message framing) is a theme that can be used for cause and effect communications. ➥ Support a prediction. Similar to cause and effect, data can be used to communicate the expected positive impact of a changed or new program or policy, particularly when the program’s or policy’s magnitude will be large. The control and hope theme, therefore, also is useful to support predictions. ➥ Evaluate. Evaluation and other types of data can be used to communicate the success or failure of a program or policy. The success theme (positive message framing) is used when positive trends and changes result from a particular program or policy. ➥ Maintain awareness. Use “tried and true” data items for the given situation. When possible, however, provide new data or reformulate existing data. An established public health issue or intervention can be refreshed on important anniversaries or when new relevant reports or studies are published. 39 CONCLUSION Summary Communicating health data is a vital component of the process of disseminating scientific findings to lay audiences. As we better understand the role of data in communication, the challenge becomes how to select and present data in ways that lay audiences can understand and use. This workbook presented an overview of the key findings and recommendations on how to better select and present data to lay audiences—the public, press, and policy makers. As noted previously, effective communication starts with having a clear story-line, a communication purpose, and a strong understanding of your audience. Knowing the characteristics of the audience, the factors that influence communication about health, and audiences’ expectations for receiving data, are critical to knowing how to communicate data. Having an understanding of audience tendencies and biases is important as those factors influence how and when to interpret data. Audience research will help you decide to what extent, if any, data should be used to convey the message with your specific audience. Defining the communication requirements for specific situations, such as unexpected events or policy planning, and understanding the context or circumstances surrounding the issue is essential, as this will influence how the data are presented. These contextual factors will help guide the approach for communicating the data (e.g., to educate or to persuade) and will help determine the selection of data elements to present to your audience. When presenting data in a visual format, features such as graphs, charts, and maps can be added to enhance a data presentation. Conversely, there are ways of communicating data without using numbers or graphics. Knowing the benefits and limitations of each approach and when to use such visualization or narrative techniques depends not only on the type of data that are available, but also on your audience and your purpose for communicating the data. Future trends and challenges Access to more health data, especially at the community level, has its benefits. It can enable communities to identify and observe what is currently occurring with respect to health indicators, and empowers them to advocate for improvements. Further, additional data can satisfy those who need more information to make key decisions or conclusions, such as local policy makers. However, challenges arise about how all of these data are synthesized and interpreted. With the quantity of health data becoming more widely available, the presentation quality of these data becomes even more important. The variety of forms in which data are available today can be misused, misinterpreted, or poorly understood. Moreover, questions may arise about how much data are needed to convey a message, or when too much or too little data are being used, given the large amount of health data that are available for some health issues. 40 Innovations in computer and other technological interfaces reflect the new wave of opportunities for data to impact health. Patient health data in electronic medical records can prompt clinicians to recommend screenings, support decision-making on treatment, and monitor adherence to treatment protocols. At the population level, data from health systems, coupled with other surveillance systems, can uncover health disparities and further prompt action toward achieving health equity. With these innovations in health information technology, communicating data effectively that will enable lay audiences to understand and be empowered may be the biggest challenge confronting researchers and practitioners. Closing Communicating health data to lay audiences is a complex process, especially when taking into account the context and other considerations associated with the data, health topic, or environment. You must carefully consider all of these factors before deciding whether data should be used in key messages, what data to communicate, and how to present selected data effectively. For public health professionals, it is always helpful to have an approach like the OPT-In framework that helps guide the planning and implementation of communication tasks. This framework can be readily used to communicate data and other health information across settings and in a variety of different situations. We hope this framework, along with the content and the practical exercises, helps promote your understanding of the concepts outlined in this workbook and can increase your ability to successfully apply them in your work. References Introduction 1 Nelson DE, Hesse BW, Croyle RT. Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press. New York, NY: Oxford University Press; 2009. Chapter 1 2 Kahneman D, Slovic P, Tversky A, ed. Judgment under Uncertainty: Heuristics and Biases. Cambridge, UK: Cambridge University Press; 1982. Slovic P. The Perception of Risk. London; Sterling, VA: Earthscan; 2000. 3 Miller JD, Kimmel LG. Biomedical Communications: Purposes, Methods, and Strategies. San Diego, CA: Academic Press; 2001. Chapter 2 4 Hornik RC, ed. Public Health Communication: Evidence for Behavior Change. Mahwah, NJ: L. Erlbaum Associates; 2002. Additional sources for Figure 2.1: Littlejohn SW, Foss KA. Theories of Human Communication. 9th ed. Belmont, CA: Wadsworth; 2007. McQuail D. McQuail’s Mass Communication Theory. 5th ed. London, UK: Sage; 2005. Additional sources for Table 2.3: Arceneaux K. The “gender gap” in state legislative representation: New data to tackle an old question. Polit Res Q. 2001;54:143–160. 41 Armor S. More women at the top. USA Today. June 25, 2003. Sect. 3. Bacharach S, Lawler E. Power and Politics in Organizations. San Francisco, CA: Jossey-Bass; 1980. Blum D, Knudson M, Henig RM, eds. A Field Guide for Science Writers: The Official Guide of the National Association of Science Writers. 2nd ed. New York, NY: Oxford University Press; 2006. Brownson RC, Malone BR. Communicating public health information to policy makers. In: Nelson DE, Brownson RC, Remington PL, Parvanta C, eds. Communicating Public Health Information Effectively: A Guide for Practitioners. Washington, DC: American Public Health Association; 2002:97–114. Dumro R, Duke S. The Web and e-mail in science communication. Science Communication. 2003;24:283-308. Friedman SM, Dunwoody S, Rogers CL, editor. Scientists and Journalists: Reporting Science as News. New York, NY: Free Press; 1986. Gastel B. Health Writer’s Handbook. Ames, IA: Iowa State University Press; 1998. Greenwell M. Communicating public health information to the news media. In: Nelson DE, Brownson RC, Remington PL, Parvanta C, eds. Communicating Public Health Information Effectively: A Guide for Practitioners. Washington, DC: American Public Health Association; 2002:73–96. Harris TE. Applied Organizational Communication: Principles and Pragmatics for Future Practice. Mahwah, NJ: Lawrence Erlbaum; 2002. Manning P. News and News Sources: A Critical Introduction. Thousand Oaks, CA: Sage; 2001. Morgan G. Images of Organizations. 2nd ed. Thousand Oaks, CA: Sage; 1997. Spasoff RA. Epidemiologic Methods for Health Policy. New York, NY: Oxford University Press; 1999. Stone DA. Policy Paradox: The Art of Political Decision Making. Rev. ed. New York, NY: Norton; 2002. Weissert CS, Weissert WG. State legislative staff influence in health policy making. J Health Polit Policy Law. 2000;25:1121–1148. Chapter 3 5 Paling J. Strategies to help patients understand risks. BMJ. 2003;327(7417):745-748. Rothman AJ, Kiviniemi MT. Treating people with information: An analysis and review of approaches to communicating health risk information. J Natl Cancer Inst Monogr. 1999(25):44-51. Sandman PM, Weinstein ND, Hallman WK. Communications to reduce risk underestimation and overestimation. Risk Decis Policy. 1998;3:93-108. 6 Schwartz LM, Woloshin S. The case for letting information speak for itself. Eff Clin Pract. 2001;4(2):76-79. Schwartz LM, Woloshin S, Black WC, Welch HG. The role of numeracy in understanding the benefit of screening mammography. Ann Intern Med. 1997;127(11):966-972. Woloshin S, Schwartz LM, Moncur M, Gabriel S, Tosteson AN. Assessing values for health: Numeracy matters. Med Decis Making. 2001;21(5):382-390. 7 Engle RW, Tuholski SW, Laughlin JE, Conway ARA. Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. J Exp Psychol Gen. 1999;128(3):309-331. Miller GA. The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychol Rev. 1956;63:81-97. 8 Hastie R, Dawes RM. Rational Choice in an Uncertain World: The Psychology of Judgment and Decision Making. Thousand Oaks, CA: Sage; 2001. Plous S. The Psychology of Judgment and Decision Making. Philadelphia, PA; Temple University Press; 1993. 9 Eveland W, Cortese J, Park J, Dunwoody S. How Web site organization influences free recall, factual knowledge, and knowledge structure. Hum Commun Res. 2004;30(2):208-233. Nielsen J. Designing Web Usability. Indianapolis, IN: New Riders; 2000. 44 Notes: s wey Pro - 5a} acs or hese NIH Publication No. 11-7724 Printed September 2011 lM 24 ll